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Orbav · AI Readiness Report

Your readiness report

Reference sample00 · Generated 2026-08-13 · Worked example — synthetic answers

This is the instrument’s real output on a fixed set of example answers — shown so you can see exactly what you get before you give us anything. It describes no company, no client, and no measured business. Yours will look exactly like this, minus this notice.

56/100

Ready ground — sequence carefully

Several of your answers describe systems a build could stand on. What decides payback now is picking the right first target, not the ground it stands on.

The four dimensions

Data readiness

33/100

Real opportunities, with gaps attached

Named systems exist, but ownership, conflicts or access still leak effort. A build is possible; some plumbing should come first.

Process automation potential

67/100

Ready ground — sequence carefully

Your answers describe repeated, mostly-documented work with someone noticing failures — the shape automation pays back on.

AI use-case fit

78/100

Strong footing

Unstructured input, human review already in the loop, simpler tools already exhausted — your answers describe a strong model fit.

Risk and compliance posture

44/100

Real opportunities, with gaps attached

Some controls exist on paper, but ownership or rollback is incomplete — known gaps, and closable before or during a first build.

Your top 3 automation opportunities

Ranked by likely payback, from your answers — and each one ends the same way: book a call to scope it, and the call is free.

  1. Opportunity 1

    Fix the data foundation before anything is built on it

    Your answers on the data questions are what hold every other score back — anything built on top would inherit the gaps. Fixing the ground first is cheaper than rebuilding on it later.

    First step. A CRM/data plumbing build puts one system of record underneath the work. From $10,000.

    See how we run it

  2. Opportunity 2

    Automate the repeated manual process end to end

    You told us things repeat the same way every time (“Several — and the variation is the exception”) — repeated, stable work is where a workflow pays for itself first.

    First step. This is the Automation Sprint’s exact shape: one workflow, fixed scope, 2–4 weeks. Sprints $5,000 · programs from $10,000.

    See how we run it

  3. Opportunity 3

    Make failures visible before a customer or a number does

    Asked how you find out when the process goes wrong, you answered “Someone stumbles on it during unrelated work”. Retries, error routing and a dead-letter queue change that answer to “the same day”.

    First step. Not a separate product — it is how we already build (see the methodology’s guard and monitor sections), and it is in scope on any Sprint or build.

    See how we run it

What this score is — and isn’t

This report reads your answers, not your systems. It is a structured self-assessment: the scores rank what you told us, on an equal-weighted model we publish, verified by nothing except you. It is not a measurement of your business, and no one at Orbav has observed your data, processes or tools. Where it says something is worth building first, treat that as the start of a conversation — the conversation is free.

This copy is the sample: the answers behind it are a fixed example set chosen to show the instrument working, not anyone’s business.

When you want a read of the systems themselves — that’s a scoping call, and it costs nothing.